Skill UI

This comprehensive workflow guides the design, optimization, and deployment of scalable, cost-effective Google Cloud Platform (GCP) architectures for both startups and large enterprises. It covers the full lifecycle, from gathering detailed requirements (compliance, SLA) and recommending optimal patterns (Serverless, GKE, Data Pipelines) to estimating costs, generating Infrastructure as Code (IaC) using Terraform, setting up CI/CD pipelines, and completing a thorough security review.

A powerful operational companion for database developers. This skill assists with the daily lifecycle of database interactions, including translating natural language requirements into optimized SQL queries, generating database migrations, performing comprehensive schema introspection across multiple dialects (PostgreSQL, MySQL, SQLite, SQL Server), and identifying performance bottlenecks through detailed query optimization and index recommendations. It also supports ORM patterns like Prisma and SQLAlchemy.

AgentFlow transforms your existing Kanban board (Asana, GitHub, Linear) into a self-managing, autonomous AI development pipeline. It orchestrates multiple AI agents through defined stages (Backlog to Done), enforcing deterministic quality gates, performing adversarial reviews, and tracking costs—all visible within your existing project management UI. It provides crash-proof execution and full observability for complex software development lifecycles.

This skill provides comprehensive automation for managing GitHub workflows across the entire development lifecycle. It covers detailed issue triage, PR review status checks, CI/CD failure debugging, official release management, and security monitoring using the GitHub CLI. Ideal for maintaining open-source project health and streamlining team development processes.

This comprehensive guide details the implementation of Firebase In-App Messaging within Flutter applications. It covers setup, programmatic message triggering and suppression during critical flows (like payments), and essential privacy controls for GDPR compliance. Learn best practices for testing campaigns, utilizing A/B testing, and managing the full lifecycle of in-app message campaigns.

This comprehensive guide provides an end-to-end solution for implementing Firebase Cloud Messaging (FCM) in Flutter applications. It covers platform-specific setup for iOS, Android, and Web, detailing how to handle messages in foreground, background, and terminated states. Key topics include managing notification permissions, handling token lifecycles, and implementing reliable cross-platform push notification logic.

Provides comprehensive guidelines on using Go's `context.Context` for managing request lifecycles. Learn how to correctly propagate cancellation signals, enforce deadlines, handle timeouts, and safely pass request-scoped values across API boundaries (HTTP handlers, services, databases). Essential reading for writing resilient and robust concurrent Go applications.

This comprehensive guide covers Dependency Injection (DI) patterns specifically for Golang. It explains why DI is crucial for building testable, loosely coupled, and maintainable services. The skill compares manual constructor injection for small projects with advanced DI libraries (like google/wire, uber-go/dig) for complex architectures, focusing on best practices such as interface-based design and managing service lifecycles.

A type-safe dependency injection toolkit for Go, enabling robust and maintainable application architecture. It manages service containers, handling service lifecycles (Lazy, Eager, Transient), scoped services, and dependency resolution. Ideal for refactoring manual constructor injection into a structured DI system in Go projects.

This comprehensive guide deep dives into `stretchr/testify`, the essential tool for writing robust and readable unit tests in Go. It covers the crucial differences between `assert` and `require` for controlled failure handling, implementing sophisticated mocks, and managing test lifecycles using suites. It is perfect for developers aiming to write maintainable, self-documenting, and reliable test code in Go.

Guides Flutter/Dart developers through Riverpod setup and best practices for defining providers, using refs, handling lifecycles, combining async data, performing side effects, observing changes, and testing so app state stays consistent and leak-free.

A comprehensive workflow for the full lifecycle management of AI skills. This tool guides users through creating skills from scratch, modifying existing ones, and rigorously benchmarking performance. It supports iterative refinement, quantitative evaluation, and optimizing skill descriptions for maximum triggering accuracy.